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import pytest

import numpy as np
import os
import torch
from brevitas.core.quant import QuantType
from brevitas.export import export_qonnx
from brevitas.nn import QuantLinear
from qonnx.core.datatype import DataType
from qonnx.core.modelwrapper import ModelWrapper
from qonnx.transformation.infer_shapes import InferShapes
from qonnx.util.basic import gen_finn_dt_tensor
from qonnx.util.cleanup import cleanup as qonnx_cleanup

import finn.core.onnx_exec as oxe
from finn.transformation.qonnx.convert_qonnx_to_finn import ConvertQONNXtoFINN

export_onnx_path = "test_brevitas_qlinear.onnx"


@pytest.mark.brevitas_export
@pytest.mark.parametrize("bias", [False, True])
@pytest.mark.parametrize("out_features", [4])
@pytest.mark.parametrize("in_features", [3])
@pytest.mark.parametrize("w_bits", [4])
@pytest.mark.parametrize("i_dtype", [DataType["UINT4"]])
def test_brevitas_qlinear(bias, out_features, in_features, w_bits, i_dtype):
    i_shape = (1, in_features)
    w_shape = (out_features, in_features)
    b_linear = QuantLinear(
        out_features=out_features,
        in_features=in_features,
        bias=bias,
        bias_quant_type=QuantType.FP,
        weight_bit_width=w_bits,
        weight_quant_type=QuantType.INT,
        weight_scaling_per_output_channel=True,
    )
    weight_tensor_fp = np.random.uniform(low=-1.0, high=1.0, size=w_shape).astype(np.float32)
    b_linear.weight.data = torch.from_numpy(weight_tensor_fp)
    b_linear.eval()
    m_path = export_onnx_path
    export_qonnx(b_linear, torch.randn(i_shape), m_path)
    qonnx_cleanup(m_path, out_file=m_path)
    model = ModelWrapper(m_path)
    model = model.transform(ConvertQONNXtoFINN())
    model = model.transform(InferShapes())
    inp_tensor = gen_finn_dt_tensor(i_dtype, i_shape)
    idict = {model.graph.input[0].name: inp_tensor}
    odict = oxe.execute_onnx(model, idict, True)
    produced = odict[model.graph.output[0].name]
    inp_tensor = torch.from_numpy(inp_tensor).float()
    expected = b_linear.forward(inp_tensor).detach().numpy()

    assert np.isclose(produced, expected, atol=1e-3).all()
    os.remove(export_onnx_path)
